1 XML Based Networking Method for Connecting Distributed Anthropometric Databases 24 October 2006...
-
Upload
britton-mckenzie -
Category
Documents
-
view
213 -
download
0
Transcript of 1 XML Based Networking Method for Connecting Distributed Anthropometric Databases 24 October 2006...
1
XML Based Networking Method for Connecting Distributed Anthropometric
Databases 24 October 2006
Huaining Cheng
Dr. Kathleen M. RobinetteHuman Effectiveness Directorate
Air Force Research Laboratory
Approved for public release; distribution is unlimited. AFRL-WS 06-2387 (Oct 13 2006)
2
Overview
• Integration issues
• Solution options with pros and cons
• WEAR short-term solutions
• WEAR long-term solution
• Summary
3
WEAR Group
• WEAR stands for World Engineering Anthropometry Resources
– A nonprofit organization based in France to promote sharing and using of its members’ anthropometry resources
– A dozen members located around world
– Members have huge collection of anthropometry survey data over large span of time
4
Integration Issues
• Data extraction and search
• Network accessibility
• Data representation
• Data quality
• Security
• Data analysis
• Data autonomy
• Financial and manpower constraints
5
Integration Solution Options
• Examine three possible integration solutions for the WEAR group integration
– Linked servers
– Data warehouse
– Service-oriented architecture (XML Web services)
• Examine how the solutions can address the above integration issues
• Envision potential anthropometry applications for the integrated WEAR
6
Linked Server Structure
• Use four-part name syntax in a query instead of only table name
– LinkedServerName
– DatabaseName
– Owner
– TableName
REF 1: “Configuring Linked Servers,” Microsoft MSDN Library, http://msdn.microsoft.com/library/default.asp?url=/library/en-us/adminsql/ad_1_server_4uuq.asp
7
Linked Server Pros & Cons
• Advantages – conceptually easy
– The ability to issue distributed queries and transactions on heterogeneous data sources across the enterprise
• Disadvantages – tight integration and direct access
– Maintenance and update nightmare
– No data autonomy
– Require direct access and reliable connection
8
Data Warehouse
• Main objective of data warehouse is business intelligence analysis of integrated data over time
– Business trend and variance analysis through OLAP (On-Line Analytical Processing)
– Data mining – automated discovery of implicit patterns and interesting knowledge hidden in the large amounts of data
9
Data Warehouses
• Characteristics of data warehouse
– Specialized database built on top of operational databases.
– Integration process through ETL (Extract, Transform, and Load)
– Optimized for over time data analysis
– Highly normalized structure
10
Anthropometry Star Schema
• Anthropometry database application of star schema
– Find groups of anthropometry measurements as biometrics identifier
Birth_Place_Key
Ethnicity_Key
Gender_Key
Age_Key
Measurement_1
Measurement_2
…
Landmark_1
Landmark_2
…
Measurement Fact
Birth_Place_Key
City
Province_or_State
Country
Geographical_Region
Birth Place Dimension
Ethnicity_Key
Ethnicity_Name
Ethnicity_Description
Ethnicity Dimension
Gender_Key
Gender
Gender Dimension
Age_Key
Starting_Age
Ending_Age
Age Dimension
Birth_Place_Key
Ethnicity_Key
Gender_Key
Age_Key
Measurement_1
Measurement_2
…
Landmark_1
Landmark_2
…
Measurement Fact
Birth_Place_Key
Ethnicity_Key
Gender_Key
Age_Key
Measurement_1
Measurement_2
…
Landmark_1
Landmark_2
…
Measurement Fact
Birth_Place_Key
City
Province_or_State
Country
Geographical_Region
Birth Place Dimension
Ethnicity_Key
Ethnicity_Name
Ethnicity_Description
Ethnicity Dimension
Ethnicity_Key
Ethnicity_Name
Ethnicity_Description
Ethnicity Dimension
Gender_Key
Gender
Gender Dimension
Gender_Key
Gender
Gender Dimension
Age_Key
Starting_Age
Ending_Age
Age Dimension
Age_Key
Starting_Age
Ending_Age
Age Dimension
11
Data Warehouse Pros & Cons
• Advantages – strong analytical capability
– A platform for many potential anthropometry applications of OLAP and data mining
• Disadvantages – tight integration and high cost
– Difficult to build ETL processes with various systems platforms and database structures as well as different locales
– Lack of data autonomy
12
Web Service Architecture
• Web service architecture adheres to the principles of service-orientation
– Services are loosely coupled, autonomous, stateless, and discoverable.
• Consists of three basic types of entities
– Service requestor, service provider, and service registry
– Communicate through TCP/IP
13
WEAR Application of Web Services
• Member 1 requests survey data & shape descriptors
Service Registry
Member 2
Italy Survey
Member 3
Netherland Survey
Member 4
Shape Descriptor Tool
Member 1
US Survey
Publish WSDL
Publish WSDL
Publish WSDL
Publish WSDL
Discover and Retrieve WSDL
Discover and Retrieve WSDL
SOAP Message
Request Survey
SOAP Message Return Survey Data
SO
AP
Mes
sage
-R
eque
st S
urve
y
SO
AP
Mes
sage
R
etur
n S
urve
y D
ata
SOAP Message - Request Calculation of Shape Descriptor and Data
SOAP Message - Return Shape Descriptor & Data
2
3
4
1
5
6
4
5Service RegistryService Registry
Member 2
Italy Survey
Member 3
Netherland Survey
Member 4
Shape Descriptor Tool
Member 1
US Survey
Publish WSDL
Publish WSDL
Publish WSDL
Publish WSDL
Discover and Retrieve WSDL
Discover and Retrieve WSDL
SOAP Message
Request Survey
SOAP Message Return Survey Data
SO
AP
Mes
sage
-R
eque
st S
urve
y
SO
AP
Mes
sage
R
etur
n S
urve
y D
ata
SOAP Message - Request Calculation of Shape Descriptor and Data
SOAP Message - Return Shape Descriptor & Data
22
33
44
11
55
66
44
55
14
Loosely Coupled Integration
• XML Web service architecture is a loosely coupled integration
– Integration is done through the service contract (WSDL) instead of open connection
– Work is requested/delivered as payloads in the SOAP messages
– Messaging mechanism brings
• Autonomy
• Statelessness
15
Web Services Pros & Cons
• Advantages – autonomy and scalability
– Solve the problems that are difficult to handle by a tight integration
• Disadvantages – security and performance
– Challenge in performing and propagating user authentication and authorization
– XML documents are slow to create and process
– Evolving standards and specifications
16
WEAR Integration ObjectivesShort-Term
• Real world – two types of integrations
– Enterprise systems integration
– Business to business (B2B) integration
• Short-term WEAR integration objectives
– Integrate and share anthropometry survey data automatically
– WEAR members maintain and control independently their databases and existing web application
17
WEAR Integration Solution Short-Term
• WEAR has to be treated as a federation
• Web service architecture is inherently federated because of its loosely coupled nature
– Best solution to make the WEAR integration satisfy the short-term objectives
• Universal anthropometry data sets – XML
• Autonomous
18
WEAR Integration SolutionImplementation Issues
• Limit services to data sets only without RPC (remote procedure call)
• Real-time performance is not a concern
• Use restricted UDDI registry to increase security
• Implement user authentication using X509 digital client certificate
• Implement user authorization through SOAP header
19
WEAR Integration Objectives Long-Term
• WEAR integration long-term objectives
– Build analytical models to produce anthropometry solution toolkits
– Offer these toolkits as Web services accessible by the public and special industry groups
20
WEAR Hybrid Web Service / Data Mart Model
Service Registry
Member 2
Italy Survey
Member 3
Netherland Survey
Member 4
Shape Descriptor Tool
Member 1
US Survey
Publish WSDL
Publish WSDL
Publish WSDL
Publish WSDL
Discover and Retrieve WSDL
Discover and Retrieve WSDL
SOAP Message
Request Survey
SOAP Message Return Survey Data
SO
AP
Mes
sage
-R
eque
st S
urve
y
SO
AP
Mes
sage
R
etur
n S
urve
y D
ata
SOAP Message - Request Calculation of Shape Descriptor and Data
SOAP Message - Return Shape Descriptor & Data
2
3
4
1
5
6
4
5Service RegistryService Registry
Member 2
Italy Survey
Member 3
Netherland Survey
Member 4
Shape Descriptor Tool
Member 1
US Survey
Publish WSDL
Publish WSDL
Publish WSDL
Publish WSDL
Discover and Retrieve WSDL
Discover and Retrieve WSDL
SOAP Message
Request Survey
SOAP Message Return Survey Data
SO
AP
Mes
sage
-R
eque
st S
urve
y
SO
AP
Mes
sage
R
etur
n S
urve
y D
ata
SOAP Message - Request Calculation of Shape Descriptor and Data
SOAP Message - Return Shape Descriptor & Data
22
33
44
11
55
66
44
55
Birth_Place_Key
Ethnicity_Key
Gender_Key
Age_Key
Measurement_1
Measurement_2
…
Landmark_1
Landmark_2
…
Measurement Fact
Birth_Place_Key
City
Province_or_State
Country
Geographical_Region
Birth Place Dimension
Ethnicity_Key
Ethnicity_Name
Ethnicity_Description
Ethnicity Dimension
Gender_Key
Gender
Gender Dimension
Age_Key
Starting_Age
Ending_Age
Age Dimension
Birth_Place_Key
Ethnicity_Key
Gender_Key
Age_Key
Measurement_1
Measurement_2
…
Landmark_1
Landmark_2
…
Measurement Fact
Birth_Place_Key
Ethnicity_Key
Gender_Key
Age_Key
Measurement_1
Measurement_2
…
Landmark_1
Landmark_2
…
Measurement Fact
Birth_Place_Key
City
Province_or_State
Country
Geographical_Region
Birth Place Dimension
Ethnicity_Key
Ethnicity_Name
Ethnicity_Description
Ethnicity Dimension
Ethnicity_Key
Ethnicity_Name
Ethnicity_Description
Ethnicity Dimension
Gender_Key
Gender
Gender Dimension
Gender_Key
Gender
Gender Dimension
Age_Key
Starting_Age
Ending_Age
Age Dimension
Age_Key
Starting_Age
Ending_Age
Age Dimension
Member A (Data Marts)
Discover and Retrieve WSDL
Data Feeds
(SOAP Message)
External Web Service Client
Public UDDI Registry
Publish WSDL
Discover and Retrieve WSDL
SOAP Message Request Datasets/Toolkits
SOAP Message Return Solutions
Replicate public accessible web services registration
SO
AP
Mes
sage
R
eque
st D
atas
ets/
Too
lkits
SO
AP
Mes
sage
R
etur
n S
olut
ions
Service Registry
Member 2
Italy Survey
Member 3
Netherland Survey
Member 4
Shape Descriptor Tool
Member 1
US Survey
Publish WSDL
Publish WSDL
Publish WSDL
Publish WSDL
Discover and Retrieve WSDL
Discover and Retrieve WSDL
SOAP Message
Request Survey
SOAP Message Return Survey Data
SO
AP
Mes
sage
-R
eque
st S
urve
y
SO
AP
Mes
sage
R
etur
n S
urve
y D
ata
SOAP Message - Request Calculation of Shape Descriptor and Data
SOAP Message - Return Shape Descriptor & Data
2
3
4
1
5
6
4
5Service RegistryService Registry
Member 2
Italy Survey
Member 3
Netherland Survey
Member 4
Shape Descriptor Tool
Member 1
US Survey
Publish WSDL
Publish WSDL
Publish WSDL
Publish WSDL
Discover and Retrieve WSDL
Discover and Retrieve WSDL
SOAP Message
Request Survey
SOAP Message Return Survey Data
SO
AP
Mes
sage
-R
eque
st S
urve
y
SO
AP
Mes
sage
R
etur
n S
urve
y D
ata
SOAP Message - Request Calculation of Shape Descriptor and Data
SOAP Message - Return Shape Descriptor & Data
22
33
44
11
55
66
44
55
Birth_Place_Key
Ethnicity_Key
Gender_Key
Age_Key
Measurement_1
Measurement_2
…
Landmark_1
Landmark_2
…
Measurement Fact
Birth_Place_Key
City
Province_or_State
Country
Geographical_Region
Birth Place Dimension
Ethnicity_Key
Ethnicity_Name
Ethnicity_Description
Ethnicity Dimension
Gender_Key
Gender
Gender Dimension
Age_Key
Starting_Age
Ending_Age
Age Dimension
Birth_Place_Key
Ethnicity_Key
Gender_Key
Age_Key
Measurement_1
Measurement_2
…
Landmark_1
Landmark_2
…
Measurement Fact
Birth_Place_Key
Ethnicity_Key
Gender_Key
Age_Key
Measurement_1
Measurement_2
…
Landmark_1
Landmark_2
…
Measurement Fact
Birth_Place_Key
City
Province_or_State
Country
Geographical_Region
Birth Place Dimension
Ethnicity_Key
Ethnicity_Name
Ethnicity_Description
Ethnicity Dimension
Ethnicity_Key
Ethnicity_Name
Ethnicity_Description
Ethnicity Dimension
Gender_Key
Gender
Gender Dimension
Gender_Key
Gender
Gender Dimension
Age_Key
Starting_Age
Ending_Age
Age Dimension
Age_Key
Starting_Age
Ending_Age
Age Dimension
Member A (Data Marts)
Birth_Place_Key
Ethnicity_Key
Gender_Key
Age_Key
Measurement_1
Measurement_2
…
Landmark_1
Landmark_2
…
Measurement Fact
Birth_Place_Key
City
Province_or_State
Country
Geographical_Region
Birth Place Dimension
Ethnicity_Key
Ethnicity_Name
Ethnicity_Description
Ethnicity Dimension
Gender_Key
Gender
Gender Dimension
Age_Key
Starting_Age
Ending_Age
Age Dimension
Birth_Place_Key
Ethnicity_Key
Gender_Key
Age_Key
Measurement_1
Measurement_2
…
Landmark_1
Landmark_2
…
Measurement Fact
Birth_Place_Key
Ethnicity_Key
Gender_Key
Age_Key
Measurement_1
Measurement_2
…
Landmark_1
Landmark_2
…
Measurement Fact
Birth_Place_Key
City
Province_or_State
Country
Geographical_Region
Birth Place Dimension
Ethnicity_Key
Ethnicity_Name
Ethnicity_Description
Ethnicity Dimension
Ethnicity_Key
Ethnicity_Name
Ethnicity_Description
Ethnicity Dimension
Gender_Key
Gender
Gender Dimension
Gender_Key
Gender
Gender Dimension
Age_Key
Starting_Age
Ending_Age
Age Dimension
Age_Key
Starting_Age
Ending_Age
Age Dimension
Member A (Data Marts)
Discover and Retrieve WSDL
Data Feeds
(SOAP Message)
External Web Service Client
Public UDDI Registry
Public UDDI Registry
Publish WSDL
Discover and Retrieve WSDL
SOAP Message Request Datasets/Toolkits
SOAP Message Return Solutions
Replicate public accessible web services registration
SO
AP
Mes
sage
R
eque
st D
atas
ets/
Too
lkits
SO
AP
Mes
sage
R
etur
n S
olut
ions
21
Conclusions
• WEAR integration is a type of federated integration
• XML Web service is the best solution due to its loosely coupling nature and service orientation
• Data marts have great potential for discovery of anthropometry data
• Hybrid Web service/data mart model is a solution to combine analytical models and XML web services
• XML is the foundation of the entire integration solution